Benefited from wireless power transfer ( WPT ) and mobile-edge computing ( MEC ) , wireless powered MEC systems have attracted widespread attention. Specifically, we design an online offloading scheme based on deep reinforcement learning that maximizes the computation rate and minimizes the energy consumption of all wireless devices ( WDs) . Extensive results validate that the proposed scheme can achieve better tradeoff between energy consumption and computation delay.